Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models
42 Pages Posted: 27 Oct 2020
We propose an Adjusted Quasi-Score (AQS) method for constructing tests for homoskedasticity in spatial econometric models. We first obtain an AQS function by adjusting the score-type function from the given model to achieve unbiasedness, and then develop an Outer-Product-of-Martingale-Difference (OPMD) estimate of its variance. In standard problems where a genuine (quasi) score vector is available, the AQS-OPMD method leads to finite sample improved tests over the usual methods. More importantly in non-standard problems where a genuine (quasi) score is not available and the usual methods fail, the proposed AQS-OPMD method provides feasible solutions. The AQS tests are formally derived and asymptotic properties examined for three representative models: spatial cross-sectional, static or dynamic panel models. Monte Carlo results show that the proposed AQS tests have good finite sample properties.
Keywords: adjusted quasi-scores, fixed effects, heteroskedasticity, incidental parameters, martingale difference, non-normality, short dynamic panels, spatial effects
JEL Classification: C12, C18, C21, C23
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